Market segmentation analyses in virtual universes

ABSTRACT

This description presents techniques for performing market segmentation analyses in virtual universes. In one embodiment, a method includes collecting virtual universe data associated with interactions between avatars, entities, and objects in a virtual universe. The collecting can include recording at least some of the virtual universe data as the interactions occur, determining a criteria with which to perform a market segmentation analysis on the virtual universe data, where segmentation divides the virtual universe data into a plurality of groups. The method can also include performing the market segmentation analysis on the virtual universe data, and generating a report indicating results of the market segmentation analysis.

TECHNICAL FIELD

Embodiments of the inventive subject matter generally relate to thefield of computer systems, and more particularly, processing virtualuniverse data.

BACKGROUND

Virtual universe systems allow people to socialize and interact in avirtual universe. A virtual universe (“VU”) is a computer-basedsimulated environment intended for its residents to traverse, inhabit,and interact through the use of avatars and other constructs. Many VUsare represented using 3-D graphics and landscapes, and are populated bymany thousands of users, known as “residents.” Other terms for VUsinclude metaverses and “3D Internet.”

SUMMARY

This description presents techniques for performing market segmentationanalyses in virtual universes. In one embodiment, a method includescollecting virtual universe data associated with interactions betweenavatars, entities, and objects in a virtual universe. The collecting caninclude recording at least some of the virtual universe data as theinteractions occur, determining a criteria with which to perform amarket segmentation analysis on the virtual universe data, wheresegmentation divides the virtual universe data into a plurality ofgroups. The method can also include performing the market segmentationanalysis on the virtual universe data, and generating a reportindicating results of the market segmentation analysis.

BRIEF DESCRIPTION OF THE DRAWINGS

The present embodiments may be better understood, and numerous objects,features, and advantages made apparent to those skilled in the art byreferencing the accompanying drawings.

FIG. 1 is a block diagram illustrating how a VU can record data as anavatar moves through a virtual universe, according to some embodiments;

FIG. 2 is a block diagram illustrating a virtual universe system,according to some embodiments of the invention;

FIG. 3 is a flow diagram illustrating operations for collecting virtualuniverse data, according to some embodiments of the invention;

FIG. 4 is a flow diagram illustrating additional operations for acollecting virtual universe data, according to some embodiments of theinvention;

FIG. 5 is a flow diagram illustrating operations for performing marketsegmentation analysis using virtual universe data, according to someembodiments of the invention;

FIG. 6 illustrates an example perceptual map of avatar time in VU andmoney spent;

FIG. 7 illustrates a perceptual map of avatar activities in a VU andtime of day; and

FIG. 8 is a pie chart showing information about avatar attendees ofbusiness lectures.

DESCRIPTION OF EMBODIMENTS Introduction

VUs simulate real-world settings. In VUs, users control their avatars tointeract with objects, entities, and other avatars. For example, a usercan move her avatar into a coffee shop (entity) to buy coffee (object)and socialize with other avatars. VU entities (e.g., coffee shop) areoften associated with real-world entities that endeavor to generatereal-world revenue. Thus, a VU coffee shop may give away virtual coffeeto promote real world coffee products. The coffee shop may also generatereal-world revenue by selling virtual or real-world products in the VU.

In VU environments, computers and software facilitate all interactionsin the VUs. As a result, VU systems can record comprehensive data aboutusers. The data can indicate how a user's avatar, objects, and entitieshave interacted with other avatars, objects, entities, and other VUconstructs. The data can also track transitions between roles. Forexample, if an avatar walks from a coffee shop into a school classroom,a VU system can record the avatar's transition from “socializer” tostudent. If the avatar goes from the classroom to a retail store, the VUsystem can record the avatar's transition from student to consumer.

Real-world entities can utilize the VU user data in segmentationanalyses. Segmentation is the subdivision of a group into discretesub-groups that share similar characteristics. The entities can usemarket segmentation (also called customer segmentation) to identifyunfulfilled needs in a VU. The entities can use the VU user data toidentify under-served segments of VU users and develop uniquelyappealing products and services for the under-served segments. Thisenables cost-effective targeting of VU users with product and serviceofferings that match their needs. Such precise targeting can obviateneedless spending on ineffective mass advertising. Additionally,entities can use segmentation to develop marketing campaigns and pricingstrategies to extract maximum value from both high and low profit VUusers. The following discussion of FIG. 1 describes how a VU system canrecord data as a user's avatar changes roles and interacts with VUentities and objects.

FIG. 1 is a block diagram illustrating how a VU can record data as anavatar moves through a virtual universe, according to some embodiments.In FIG. 1, an avatar 102 moves about a virtual universe 100, interactingwith entities, objects, and other avatars. The avatar's movements areshown in four stages. During stage one, the avatar 102 is walking in aretail area that includes a coffee shop 106. Thus, the VU system recordsdata indicating that the avatar 102 has assumed a role of “shopper.”During stage two, the avatar 102 enters the coffee shop 106, purchases acup of coffee 104, and socializes with other avatars 108. In turn, theVU system records data indicating the avatar's dual role of consumer &socializer and data indicating the avatar's interaction with the coffeeshop 106 (entity), coffee 104 (object), and avatars 108.

During stage three, the avatar 102 leaves the coffee shop and walkstoward a school. Because the avatar 102 is still in the retail area, butnot socializing, the VU system records data changing the avatar's roleback to shopper. During stage four, the avatar enters the school 108 toattend a lecture. Accordingly, the VU records the avatar's transitionfrom shopper to student and the interactions with the school 108(entity) and other avatars 110. In addition to the data about roles andinteractions, the VU system can also store other data indicating time,place, conditions, etc.

The following sections will describe systems for recording VU user dataand methods for performing segmentation analyses using the VU user data.

System Architecture and Operations

FIG. 2 is a block diagram illustrating a virtual universe system,according to some embodiments of the invention. The virtual universesystem 200 includes a network 214 connected to virtual universe servers202, a virtual universe database 204, the personal computer 210, mobiletelephone 208, and mobile device 206. Each virtual universe server 202includes a VU simulation engine 218, VU data collection unit 220, and VUdata analysis unit 216. The VU simulation engine 218 can generatecontent representing virtual universes and facilitate interactions(e.g., interactions between avatars, objects, entities, etc.) in thevirtual universes. Also, the VU simulation engine 212 can receive andprocess user input from the VU clients 212.

The VU data collection unit 220 can collect data about interactions,role changes, conditions, etc. in a VU. The VU data collection unit 220can collect data using sampling techniques for a population of avatars,selected individual avatars, etc. The VU data collection unit 220 cancollect data including content-based data, time-based data, time-baseddata, and demographic-based data. Examples of these data are givenbelow. The VU data collection unit 220 can store the data in the VUdatabase 204. The VU database 204 can include a relational database orany other suitable database (e.g., flat file database, directorydatabase, etc.) for storing the VU data. The VU data analysis unit 216can use the VU data to perform market analyses, as further describedbelow.

The personal computer 210, local telephone 208, and mobile device 206each include a VU client 212. The VU client 212 can present VU contentand facilitate user interaction with VUs. In some embodiments, the VUclients 212 can exchange data (e.g., user input, content, etc.) with theVU servers 202, render VU graphics, and perform other tasks forfacilitating VUs.

Although not shown in FIG. 2, the components of the VU system 100 caninclude processors and memory. The memory may be system memory (e.g.,one or more of cache, SRAM, DRAM, zero capacitor RAM, Twin TransistorRAM, eDRAM, EDO RAM, DDR RAM, EEPROM, NRAM, RRAM, SONOS, PRAM, etc.) orany other suitable machine-readable media. In the VU servers 202, the VUsimulation engine 218, VU data collection unit 220, and VU data analysisunit 216 can reside in system memory and direct one or more processorsto perform operations described in this document. Similarly, the VUclient 212 can reside in memory of any suitable computing device anddirect the device's processor to perform operations described in thisdocument.

The VU system's components can also include buses (e.g., PCI, ISA,PCI-Express, HyperTransport®, InfiniBand®, NuBus, etc.), networkinterfaces (e.g., an ATM interface, an Ethernet interface, a Frame Relayinterface, SONET interface, wireless interface, etc.), and storagedevices (e.g., optical storage, magnetic storage, etc.).

In alternative implementations, the VU servers' components and VUclients 212 are not executed by a processor, but instead include ASICsand/or other specialized logic for performing the functionalitydescribed in this document. Furthermore, some implementations mayinclude other components, such as video cards, audio cards, additionalnetwork interfaces, peripheral devices, etc.

Some embodiments of the inventive subject matter may be provided as acomputer program product, or software, that may include amachine-readable medium having stored thereon instructions, which may beused to program a computer (or other electronic device(s)) to perform aprocess. A machine readable medium includes any mechanism for storing ortransmitting data in a form (e.g., software, processing application)readable by a machine (e.g., a computer). The machine-readable mediummay include, but is not limited to, magnetic storage medium (e.g.,floppy diskette), optical storage medium (e.g., CD-ROM); magneto-opticalstorage medium, read only memory (ROM), random access memory (RAM),erasable programmable memory (e.g., EPROM and EEPROM), flash memory, orother types of medium suitable for storing electronic instructions. Inaddition, some embodiments may be embodied in an electrical, optical,acoustical or other form of propagated signal (e.g., carrier waves,infrared signals, digital signals, etc.), or wireline, wireless, orother communications medium.

VU Data

The VU data collection unit 220 can collect data including content-baseddata, time-based data, and demographic based data. Content-based datacan include:

-   -   VU-defined settings—VU data collection units can collect VU        settings including: forced sun setting, link/unlink objects,        search places/people, privacy options, etc.    -   Vendor-defined data—VU data collection units can collect the        following information defined by vendor entities: store type,        merchandise or service offered, type of personnel (e.g. General        Manager, Security Guard, Dancers, Owners, Sales, etc . . . ),        type of activities to do (dancing, sitting on the beach), size        of business (small, medium, large), merchandise attributes, etc.    -   User-defined data—VU data collection units can collect the        following information defined by vendor entities: outlook,        landmarks, gestures, animations user owns, properties user owns,        objects user built, user's friends, group affiliations, note        cards received/sent, items in user's inventory,        clothing/appearance selections, number of times changed in        user's outfit, number of times user instant messaged with a        certain person/group, places that to which user teleports, etc.    -   Consumer data—VU data collection units can collect the following        information associated with users in their role as consumers:        surveys taken, behaviors and shopping habits, places users shop,        what users buy, who users shop with, how much users spend,        current location, previous locations/entities visited,        locations/entities most visited, locations/entities at which        most money spent, friends, groups, geography of user, spending        habits in last X days, time spent on-line, social connectivity,        joining of events, age within the VU, etc.

Time-based data includes data about VU activities and interactionsoccurring in a given time period. The time-based data can include

-   -   VU-level time-based data—VU data collection units can collect        the following information including: number of new users who        have signed up in a specified time period, number of on-line        users in the last hour, dollar value of transactions in the last        24 hours, number of new islands purchased within a given time        period, etc.    -   Vendor-level time-based data—VU data collection units can        collect the following information for given time periods: dollar        value of sales, number of units sold, number of returns, type of        returns, number of inquires, expenses, traffic, VU stock        exchange data (if a registered business), etc.    -   User-level time-based data—VU data collection units can collect        the following information for given time periods: number of new        items added to “clothing” folder, number of times an object        (e.g., party-dress) has been used, frequency of phone calls and        to whom, most common locations visited, what activities were        performed, etc.

Demographic-based data includes characteristics of avatars for a givengeographical location within a single VU or across VUs.Demographic-based data can include:

-   -   Within a single VU—VU data collection units can collect the        following information indicating the ratio of residential vs.        commercial use in mainland locations, average dollar value of        real estate per island, dollars spent per day per island, ratio        of females to males living on an island, number of customers who        visited a shopping area in the mainland headquarters vs. the        southeast branch, ratio of new members to existing users,        frequency of user login, etc.    -   Across VUs—VU data collection units can collect the following        information indicating the ratio of users from North America,        Asia, Europe and the rest of the world in Second Life® vs.        Entropia Universe or the Sims On-line™, etc.

VU Data Collection

The above-described VU systems can have nearly omniscient views of theirpopulations, as they can read data from user profiles and inventories,and track behavior and interactions. In some instances, the VU systemcan collect data passively (i.e., without avatar knowledge) or throughopt-in programs. The VU system can passively collect data by recordinginformation arising from the normal course of conducting VUs (e.g.,interactions between avatars, objects, entities, etc.). The VU systemcan also create new means for tracking desired VU data. For example, ifnot already present, the VU system can integrate logic (e.g., programcode) for collecting data beyond what is collected in the normal courseof operation. In some instances, the VU system can include configurabledata collection logic (e.g., a configurable VU data collection unit).

In some embodiments, the VU system does not collect certain data unlessusers opt-into data collection programs. The VU system can entice usersto opt-into data collection programs by offering rewards, such ascoupons, merchandise, VU money, social status, etc.

The follow discussion of FIGS. 3 and 4 describe operations forcollecting VU data. In particular, FIG. 3 describes how embodiments of aVU server can facilitate data collection, while FIG. 4 describes how VUclients can participate in data collection.

FIG. 3 is a flow diagram illustrating operations for collecting virtualuniverse data, according to some embodiments of the invention. The flow300 will be described with reference to embodiments of the VU systemshown in FIG. 2. The flow diagram 300 begins at block 302.

At block 302, a virtual universe server 202 distributes advertisementsfor a VU market research program. The advertisements can explain thedata to be collected and analyses to be performed. The VU server 220 candistribute advertisements in the VU itself (e.g., using the VUsimulation engine 218), or it can distribute advertisements via email toVU users (e.g., the VU data collection unit 220 can send email to the VUclients 212), instant messages to VU users, etc. The flow continues atblock 304. At block 304, the VU server 202 receives users' consent toparticipate in the VU market research program. In some instances, theserver's VU simulation engine 218 detects avatars responding toadvertisements in the virtual universe. In other instances, the server'sVU data collection unit 220 receives messages including users' consent.The flow continues at block 306.

At block 306, the server's VU data collection unit 220 stores indiciaidentifying the participating users. For example, the VU data collectionunit 220 can mark fields in the participating users' records in the VUdatabase 204. The VU data collection unit 220 can also add recordsassociated with the participating users and/or perform other operationsto identify users participating in the market research program. The flowcontinues at block 308.

At block 308, the server's VU simulation engine 218 performs operationsfor facilitating the participating users' interactions and activities inthe VU. That is, the VU simulation engine 218 performs operationsenabling the participating users' avatars to move about the VU, interactwith entities, objects, and other VU constructs (e.g., see FIG. 1). Forsimplicity, the flow 300 shows this as a single operation. However, theVU simulation engine 218 may performs numerous operations and exchangevolumes of data (e.g., with the VU clients 212) to facilitate activitiesand interactions of the participating users. The flow continues at block310. At block 310, the server's VU data collection unit 220 storesinformation indicating the participating users' activities andinteractions in the VU. In some instances, the VU data collection unit220 can work in concert with the simulation engine 218. As thesimulation engine 218 performs operations for facilitating the VU, theVU data collection unit 220 stores whatever data is needed for theresearch program. The data can be stored in real-time and can includeany of the data discussed above or any other suitable data. Depending onthe market research program, the VU server 202 may collect data for aspecified period of time, specified number of transactions, underspecified conditions, etc. For simplicity, the flow 300 shows this as asingle operation. The flow continues at block 312.

At block 312, the server's VU data collection unit 220 distributesrewards to the user to participate in the market research program. Therewards can include coupons, credits/money redeemable in the VU,privileges, status, or any other suitable reward. The VU data collectionunit 220 can distribute the rewards via real-world methods (e.g., mail)by updating/adding information to the users' account records in the VUdatabase 204. From block 312, flow ends.

While FIG. 3 describes how VU servers can participate in datacollection, the discussion continues a description of how some VUclients can interact with the VU servers to collect data.

FIG. 4 is a flow diagram illustrating additional operations for acollecting virtual universe data, according to some embodiments of theinvention. The flow 400 will be described with reference to embodimentsof the VU system shown in FIG. 2. The flow begins at block 402.

At block 402, a VU client 212 presents an advertisement for marketresearch program. In some embodiments, the VU client 212 receives theadvertisement from a VU server 202. In some cases, the VU client 212graphically presents the advertisement in a graphical user interface.The advertisement can include a consent form or other means by which auser can sign-up for the market research program. The flow continues atblock 404.

At block 404, the VU client 212 receives a users consent to participatein the market research program and transmits the consent to the VUserver 202. The user may consent to the market research program byselecting options in a graphical user interface or through othersuitable means. Although not shown in FIG. 4, if the user does notconsent to the market research program, the flow would terminate. Theflow continues at block 406.

At block 406, the VU client 212 exchanges information about the user'sinteractions and activities in a virtual universe. As noted above, thiscan include user input and other information for enabling the user'savatars to move about the VU, interact with entities, objects, and otherVU constructs (e.g., see FIG. 1). For simplicity, the flow 400 showsthis as a single operation. The flow continues at block 408.

At block 408, the VU client 212 presents an indication of a reward forparticipating in the market research program. In some instances, the VUclient 212 may detect information (e.g., a message from the VU server202) indicating an award for the user. In turn, the VU client 212presents the information in a graphical user interface. From block 408,the flow ends.

Although the discussion above describes the flow 300 being performed bya VU server and the flow 400 being performed by a VU client, in someinstances, the flows are performed by other system components andalternatives to those shown in FIG. 2.

VU Data Analysis

FIG. 5 is a flow diagram illustrating operations for performing marketsegmentation analysis using virtual universe data, according to someembodiments of the invention. The flow 500 will be described withreference to embodiments of the VU system shown in FIG. 2. The flowbegins at block 502.

At block 502, a VU server's VU data analysis unit 216 determinescriteria with which to segment virtual universe data. The VU dataanalysis unit 216 can segment a population using either a-priori(predetermined clusters) or post-hoc (determined by data analysis)methods. The VU data analysis unit 216 can use any suitable clusteringmethods to divide users into segments (e.g. non-overlapping,overlapping, fuzzy, hierarchical, divisive, and so forth). The marketsegmentation criterion may segment a population based on: money spentvs. time spent in a virtual universe, times of day avatars socialize vs.work, demographic data on all avatars that interacted with a certainentity in a given time, etc. (See more examples below.) The VU dataanalysis unit 216 can allow analysts to select any suitable segmentationcriteria. The flow continues at block 504.

At block 504, the VU data analysis unit 216 receives VU data associatedwith users participating in the market research program. In someembodiments, the VU data analysis unit 216 retrieves the VU data fromthe VU database 204. Alternatively, the VU data analysis unit 216 canreceive, from the VU data collection unit 220, the VU data in real-time(e.g, when the VU data is collected). The flow continues at block 506.

At block 506, the VU data analysis unit 216 performs a marketsegmentation analysis on the VU data. That is, the VU data analysis unit216 divides the relevant VU data into segments. For example, the VU dataanalysis unit 216 may divide all participating users interacting with aparticular coffee shop into certain segments based on gender, age, moneyspent, items ordered, etc. The flow continues at block 508.

At block 508, the VU data analysis unit generates a report indicatingresults of the market segmentation analysis. In some instances, thereport includes a graphical representation of the market segments, suchas pie charts, perceptual maps, bar charts, etc. The flow continues atblock 510.

At block 510, the VU data analysis unit 260 distributes the report tointerested entities. Real-world entities (e.g., retail stores operatingin the virtual universe) can use the report to tailor their products,services, advertisements, etc. in the VU and in the real world. For someembodiments in which the VU data analysis unit 216 receives VU data inreal-time (see discussion of block 504), the VU data analysis unit 216can show segmentation of a very recent data samples (e.g., avatarscurrently in a coffee shop). VU entities can use such real-time analysesto trigger profit making opportunities. For example, when a VU entitydetects the presence of a critical number of users of a certain segment(e.g., via a report from the VU data analysis unit 216), the VU entitycan offer special products and/or services. From block 510, the flowends.

EXAMPLE SEGMENTATIONS ANALYSES

Although the VU analysis units can employ any suitable clusteringmethods, the following operations illustrate one suitable clusteringmethod: 1) Select variables to report on (defined during data collectionstep above). 2) Select a distance to measure. 3) Select clusteringprocedure. 4) Determine number of clusters 5) Map conclusions, includinggraphical representations. 6) Repeat analysis as needed to verify.Having access to avatars' behavioral patterns and preferences willprovide a basis of value-added insight for potential marketers andsellers of all types. Data may be provided and presented for groups(segment of many) or individuals (i.e., as a segment-of-one).

Group Segmentation

The following discussion shows examples of how some VU data analysisunits can segment VU data.

FIG. 6 illustrates an example perceptual map of avatar time in VU andmoney spent. FIG. 6 shows a perceptual map including four segments (A,B, C and D). The data shows VU residents categorized based on the amountof time they spend in a VU and amount of money they spend.

-   -   Segment A—This segment does not spend a lot of time in the VU,        but does spend a lot of money. This segment may be interested in        using the VU to shop for items or conduct brief business        transactions, but may not stay to socialize.    -   Segment B—This segment spends a lot of time in the VU and also        spends a lot of money. These are the power users, and therefore        they may be first adopters and willing to purchase higher-end VU        items.    -   Segment C—This segment does not spend a lot of time in the VU        and does not spend a lot of money. Marketers may choose not to        invest in marketing to this segment.    -   Segment D—This segment spends a lot of time in the VU, but does        not spend a lot of money. This segment is dedicated to the use        of the VU, but may be price-sensitive. Marketers may look. for        opportunities to get this group into the habit of purchasing        more, perhaps with free offers or discounts.

FIG. 7 illustrates a perceptual map of avatar activities in a VU andtime of day. The perceptual map shows four segments (A, B, C and D)categorized based avatar activity type and time of day the activitiesoccur.

-   -   Segment A—Avatars in this segment socialize in the morning        hours, primarily at coffee shops and cafes. It is a relatively        small group.    -   Segment B—This is the largest segment. This segment includes        avatars who spend time in the VU socializing between 6 PM and        midnight. Avatars in this group use the VU for after-work        activities (casinos, nightclubs, concerts, etcetera) and may be        interested in information about new and future hot-spots or        shopping options.    -   Segment C—This segment includes avatars using the VU in the        morning hours (before noon) for business activities. This is the        second largest group.

The avatars may be interested in business news (VU and real-world) andalternative communication options (e.g., telepresence).

-   -   Segment D—This is the smallest segment. The avatars in this        segment use the VU for work after 12:00 PM.

In another example, a VU data analysis unit can segment data aboutavatar attendees of a school's business lectures during the last 2 weekperiod. This example shows how the VU system, with its vast datacollection capabilities, can accurately track role transitions, such asstudent to socializer. FIG. 8 is a pie chart showing information aboutavatar attendees of business lectures. The segmentation data reveals thefollowing: 400 attended six lectures at 7:15 PM, 70% of all attendeeswere male, 50% of all attendees went to The Hot-Spot Nightclub followingthe lecture, 75% of all attendees had personal inventories that includedstate-of-the art PDAs, 60% of all attendees own property on Island Y,and 40% of all attendees have registered for additional lecture series.

The segmentation data may suggest that marketers and service providerswho may benefit from targeting this group includes: Island Y propertysellers, Nightclubs in vicinity of the school lecture hall, and cellular& smart-phone vendors. Thus, the VU data analysis unit can distributethis data to marketers and service providers in these categories. Insome instances, marketers and service providers can use this datafor: 1) identification of best-fit “beachhead” for market entrance(beachhead=starting point to expand into other sub-segments or segments;and 2) validation of target customer segment—conduct surveys of avatarsafter initial segmentation has been done to gain insight into theircompelling reasons to buy; product/service requirements; perceivedcompetitive products etc. The data can then become part of our overallmarket segmentation database and provide further knowledge on the buyingpreferences.

Individual Segmentation

In some instances, a VU data analysis unit can perform a segmentationanalysis on a single user. The following example shows segmentation ofdata collected over a two week period for avatar Sasha Moonbeam. In thetwo week period, Sasha Moonbeam participated in the followingactivities:

-   -   Attended business lectures at HBS 3 times per week.    -   Went to Public Library on Island X after each lecture, spending        a majority of time in Political Science section.    -   Attended two campaign speeches by the same hopeful '08        presidential candidate (candidate “B”).    -   Patronizes local Joe's Buzz Coffee Shop every evening at 7 PM.    -   Personal inventory includes: 10 casual outfits, purchased at        exclusive boutiques in Island X, etc.

This data suggest that the following marketers and service providerscould benefit from targeting Sasha Moonbeam: would-be campaign fundraisers for candidate “B”, niche boutiques on Island X, politicalscience publications, business schools offering lecture series, coffeeshops with local flair and flavor.

General Concepts

While the embodiments are described with reference to variousimplementations and exploitations, it will be understood that theseembodiments are illustrative and that the scope of the inventive subjectmatter is not limited to them. In general, techniques for analyzing datain a VU, as described in this document, may be implemented withfacilities consistent with any hardware system or hardware systems. Manyvariations, modifications, additions, and improvements are possible. Insome instances, structures and functionality presented as separatecomponents in the example configurations may be implemented withcombined structures or components. Similarly, structures andfunctionality presented as a single component may be implemented asseparate components. These and other variations, modifications,additions, and improvements may fall within the scope of the inventivesubject matter. This description includes exemplary systems, methods,techniques, instruction sequences and computer program products thatembody techniques of the present inventive subject matter. However, itis understood that the described embodiments may be practiced withoutthese specific details. In some instances, for clarity, this descriptionomits certain well-known instructions, protocols, structures, andtechniques.

1. A method comprising: collecting virtual universe data associated withinteractions between avatars, entities, and objects in a virtualuniverse, the collecting including, collecting at least some of thevirtual universe data as the interactions occur; determining a criteriawith which to perform a market segmentation analysis on the virtualuniverse data, wherein segmentation divides the virtual universe datainto a plurality of groups; performing the market segmentation analysison the virtual universe data; and generating a report indicating resultsof the market segmentation analysis.
 2. The method of claim 1, whereinthe collecting further includes: distributing advertisements for amarket research program in the virtual universe; and receiving, fromusers, consent allowing collection the virtual universe data.
 3. Themethod of claim 1 wherein at least some of the collecting virtualuniverse data occurs in real-time, and wherein the market segmentationanalysis indicates information about avatars interacting with an entity,the method further comprising: transmitting the report to the entity totrigger a special offer targeted to the avatars interacting with theentity.
 4. The method of claim 1, wherein the colleting virtual universedata further includes: assigning, based on some of the interactions, afirst role to at least one of the avatars; recording the first role; andassigning, based on others of the interactions, a second role to the atleast one of the avatars.
 5. The method of claim 1, wherein virtualuniverse data indicates roles of the avatars in the virtual universe. 6.The method of claim 1, wherein the virtual universe data includes one ormore of virtual universe defined data, vendor-defined data, user-defineddata, consumer data, virtual universe time based data, and vendor-leveltime-based data.
 7. The method of claim 1 further comprising: presentinga reward to the users for giving the consent, wherein the rewardrepresents value in the virtual universe.
 8. The method of claim 1,wherein the criteria indicates how to divide the virtual universe datainto groups, and wherein the criteria include one or more of money spentby the avatars in the virtual universe, time spent in the virtualuniverse by the avatars, and roles of the avatars in the virtualuniverse.
 9. One or more machine-readable media having stored therein aprogram product, which when executed a set of one or more processorunits causes the set of one or more processor units to performoperations that comprise: collecting virtual universe data associatedwith interactions between avatars, entities, and objects in a virtualuniverse, the collecting including recording portions of the virtualuniverse data as the interactions occur; determining a criteria withwhich to perform a market segmentation analysis on the virtual universedata, wherein segmentation divides the virtual universe data into aplurality of groups; performing the market segmentation analysis on thevirtual universe data; and generating a report indicating results of themarket segmentation analysis.
 10. The one or more machine-readable mediaof claim 9, wherein the colleting virtual universe data furtherincludes: assigning, based on some of the interactions, a first role toat least one of the avatars; recording the first role; and assigning,based on others of the interactions, a second role to the at least oneof the avatars.
 11. The one or more machine-readable media of claim 9,wherein the operations further comprise: advertisements for a marketresearch program in the virtual universe; and receiving, from users,consent allowing collection the virtual universe data.
 12. The one ormore machine-readable media of claim 9, wherein the collecting virtualuniverse data occurs in real-time, and wherein the market segmentationanalysis indicates information about avatars interacting with an entity,the method further comprising: transmitting the report to the entity totrigger a special offer targeted to the avatars interacting with theentity.
 13. The one or more machine-readable media of claim 9, whereinthe virtual universe data includes one or more of virtual universedefined data, vendor-defined data, user-defined data, consumer data,virtual universe time based data, and vendor-level time-based data. 14.The one or more machine-readable media of claim 9 further comprising:presenting a reward to the users for giving the consent, wherein thereward represents value in the virtual universe.
 15. A systemcomprising: a virtual universe server including, a virtual universesimulation engine configured to facilitate interactions between avatars,entities, and objects in a virtual universe; a virtual universe datacollection unit configured to collect virtual universe data about theavatars, entities and objects, wherein the virtual universe dataindicates roles of the avatars; and a virtual universe data analysisunit configured to perform a market segmentation analysis on the virtualuniverse data, the market segmentation analysis to indicate buyinghabits of the avatars; a virtual universe client configured to receiveuser input associated with the avatars, entities, and objects, and totransmit the user input to the virtual universe server.
 16. The systemof claim 15, wherein the virtual universe data collection unit isfurther configured to procure consent from users associated with theavatars, the consent being for collection of the virtual universe data.17. The system of claim 15, wherein the virtual universe data includesone or more of virtual universe defined data, vendor-defined data,user-defined data, consumer data, virtual universe time based data, andvendor-level time-based data
 18. The system of claim 15, wherein thevirtual universe data analysis unit is also configured to distributerewards to users who consented to the collection of the virtual universedata.
 19. The system of claim 15, wherein the interactions includepurchasing goods in the virtual universe, socializing in the virtualuniverse, working in the virtual universe, and attending educationalevents in the virtual universe.
 20. The system of claim 15, wherein thevirtual universe data collection unit is further configured tocontinuously collect portions of the virtual universe data in real-time,and wherein the virtual universe simulation engine is further configuredto enable one or more of the entities to use the market segmentationanalysis to offer special products, in response to the recentlycollected portions the virtual universe data.